How Educators can Shape Edtech Development

Education technology is easy to build in theory. The real challenge is making it work in the hands of a student whose internet drops mid-lesson, or a working mum who is logging into university for the first time on a shared device. The test is not in creating EdTech tools but in making them work for the people who need them most. When we started uLesson in 2019, we built a platform with high-quality video lessons, quizzes, and practice tests. Everything worked perfectly in our offices in Jos and then, Abuja. But that changed when we tried to get them into the hands of students in towns and villages where electricity was unreliable, data was expensive, and smartphones were often shared among siblings. The same lessons appeared when we launched Miva Open University, an affordable, accessible university that delivers quality education with the same rigour as a physical campus. Creating the platform was one challenge; helping working adults adapt to digital learning for the first time was another. Some of our students had never studied without the structure of a physical classroom. Many were logging in from places where network connectivity was patchy at best. These challenges sit against a larger backdrop: According to Quartz, only 1 in 4 students applying to university will get accepted. Not because they didn’t study hard enough, instead, in many cases, it is because there simply isn’t enough room for all of them. From these experiences, I’ve learnt that successful EdTech implementation requires: - Designing for context: Tools must work offline or in low-bandwidth environments. - Investing in people: Teachers, facilitators, and students need training, support, and trust to use technology effectively. - Patience in adoption: Communities don’t adopt new systems overnight. Value has to be proven, and trust earned, over time. I remain convinced that EdTech will play a central role in the future of African learning. But for it to truly work, it must be built not just for ambition, but for reality. It has to be built for students walking kilometres to school, for families sharing a single device, and for communities learning to trust digital tools for the first time. We’re still learning. We’ll keep improving. And with each iteration, we get closer to delivering not just access, but quality learning wherever a student lives.

Something unexpected has emerged in my AI literacy research that's challenging conventional wisdom: the critical role of acculturation patterns in how AI literacy actually develops in educational settings. Most frameworks treat AI literacy as a structured set of skills to acquire - a checklist of competencies to master. But what I'm observing in classrooms and teacher workshops is something far more organic and culturally embedded. It mirrors how communities have historically adopted and adapted to new cultural tools. Let me share a pattern I've seen repeat across multiple schools: It begins with personal experimentation, often kept private. Teachers and students explore AI tools on their own, testing boundaries and building personal comfort. This phase is marked by curiosity but also hesitation - a natural part of engaging with any transformative technology. Then comes a pivotal shift: tentative sharing with trusted colleagues or peers. A teacher mentions using ChatGPT for lesson planning in the break room. A student shows a classmate how they're using AI to brainstorm essay topics. These small moments of vulnerability and exchange begin building a shared understanding. The most fascinating stage emerges next: collaborative exploration and systematic integration. Once enough individual comfort exists, communities begin collectively reimagining their practices. I watched one department move from individual experimentation to co-creating AI-enhanced curriculum units within a semester. The key wasn't just training - it was trust and shared experience. What's particularly striking is how this pattern mirrors historical educational technology adoption, from calculators to computers. Yet AI adds a unique dimension: the tool itself participates in and shapes this acculturation process. It's not just a static technology to master but an interactive partner in the learning process. This raises profound questions about how we support this cultural transition. Should we focus less on formal training and more on creating safe spaces for experimentation? How do we honor the organic nature of this process while ensuring equitable access and development? #AIResearch #EducationalChange #TeacherDevelopment #EdTech Dr. Sabba Quidwai France Q. Hoang Pat Yongpradit Mike Kentz Phillip Alcock Doan Winkel Jason Gulya Marc Watkins Sonia Kathuria MA. Ed

Excited to share some deeper thinking on a core belief that has guided our Edtech investments work at Charter School Growth Fund. Many of the most impactful new products will be built by those with the lived experience and earned insights of teaching and running schools. That's why the majority of our Edtech investments have a former charter educator or leader as a founder. These leaders know which problems are merely annoying and which ones are breaking people. They know that the last-mile design and implementation of products is often the difference between something working 80% of the time vs. 99%, and that those last percentage points are all that matter for a busy educator. This dynamic is more true now than ever, as the cost of building software has dropped dramatically and the pace of technological change is rapidly accelerating. Schools want to partner with founders who they trust know their needs inside and out. This Edtech founder's mission and values alignment can’t be overstated. The trust that comes from the educator DNA is very real. Schools want to know they are partnering with tools and solutions that are continually designed with what’s best for kids above all else. In our recent post, we profile three inspiring founders who embody this. All are in different stages of the growth journey, from serving hundreds of educators to millions. These founders didn't set out to build tech companies. They set out to solve specific challenges in their schools. The technology followed the insight, not the other way around: 🔊 Maria H. Andersen went back to the classroom Beehive Science & Technology Academy after exiting her first company — and the cognitive overload she felt teaching five preps became Socrait. This voice-powered assistant gives teachers their brainspace back. 💻 Sabina Bharwani's years at Uncommon Schools inspired her to increase access to computer science pathways and create turnkey options for schools to enhance programs beyond ELA and math. Hello World now serves 50%+ of the country's largest districts with CS and AI literacy — and 92% of students in our portfolio schools who use Hello World come from underrepresented STEM groups. 🪄 Adeel Khan founded the #1 public high school in Denver with DSST Public Schools before building MagicSchool AI, now reaching 7M+ educators in 160+ countries. He knew teachers didn't need another AI tool. They needed the blank page problem solved. We are so honored to play a small role in supporting amazing educators who are pursuing solutions to big problems at scale. Read the full piece 👇. Thank you to Elena Thurman and Jeff McGuire for your partnership on this effort. #k12 #AI #Futureoflearning #edtech https://lnkd.in/gNPDjFuV

Dear EdTech Investors - Part 3 In my last post, I told you about the 5 percent problem. Only about 5 percent of students use most edtech tools at the level needed to show results. After reading that, some might blame the product. Sometimes they are right. But often the product is fine. The problem is that nobody showed the teacher how to use it effectively. I know this because I used to be that person. Before I became a principal, I was an instructional technology coach for a large school district. My job was helping teachers integrate new tools into their classrooms. I was the bridge between the product and the practice. 𝗧𝗵𝗲 𝘁𝗼𝗼𝗹 𝘄𝗮𝘀 𝗻𝗲𝘃𝗲𝗿 𝘁𝗵𝗲 𝗵𝗮𝗿𝗱𝗲𝘀𝘁 𝗽𝗮𝗿𝘁. The hard part is fitting it into a 50-minute class with 35 students who are all in different places. The hard part is leaders making the case to staff that this tool is worth their time when they have been burned by the last three. That is where a lot of EdTech investments fail. 𝑵𝒐𝒕 𝒂𝒕 𝒕𝒉𝒆 𝒑𝒓𝒐𝒅𝒖𝒄𝒕 𝒍𝒆𝒗𝒆𝒍, 𝒃𝒖𝒕 𝒂𝒕 𝒕𝒉𝒆 𝒑𝒆𝒐𝒑𝒍𝒆 𝒍𝒆𝒗𝒆𝒍. And that means your portfolio company's churn problem might not be a product problem. It might be an implementation problem. That is fixable, and fixing it is profitable. When you evaluate a company, do you ask how they support implementation? Not a PDF guide. Not a webinar. Real, sustained training that meets teachers where they are. A product without implementation support is a product waiting to be abandoned. Here is the part that should interest you: 𝒕𝒓𝒂𝒊𝒏𝒊𝒏𝒈 𝒊𝒔 𝒏𝒐𝒕 𝒋𝒖𝒔𝒕 𝒂 𝒄𝒐𝒔𝒕. 𝑰𝒕 𝒊𝒔 𝒂 𝒓𝒆𝒗𝒆𝒏𝒖𝒆 𝒔𝒕𝒓𝒆𝒂𝒎. Because schools would pay for professional development to support successful, ongoing implementation. When a company offers training that actually helps our teachers use the tool well, we will find the money. Because it makes the tool work 𝙁𝙊𝙍 the teachers, which makes the investment worth renewing. That is recurring revenue your portfolio company is leaving on the table. The companies that get this right hire former educators. They offer onboarding that goes beyond "click here, then click here." They check in at month three. They ask teachers what is not working and actually fix it. Those companies do not have a 5 percent problem. They have loyal customers. The ones that give logins and ask teachers to go to the company website's FAQ page? They end up on my list of tools to cut. If the answer to "What is your training model?" is "We have a help desk" or "We built an AI chatbot," that is not a training model. 𝑰𝒏𝒗𝒆𝒔𝒕𝒊𝒏𝒈 𝒊𝒏 𝒄𝒐𝒎𝒑𝒂𝒏𝒊𝒆𝒔 𝒕𝒉𝒂𝒕 𝒊𝒏𝒗𝒆𝒔𝒕 𝒊𝒏 𝒑𝒆𝒐𝒑𝒍𝒆 𝑾𝑰𝑳𝑳 𝒎𝒂𝒌𝒆 𝒚𝒐𝒖 𝒎𝒐𝒓𝒆 𝒎𝒐𝒏𝒆𝒚 𝒊𝒏 𝒕𝒉𝒆 𝒍𝒐𝒏𝒈 𝒓𝒖𝒏. Because that is how you build a company that schools keep for a decade. #EdTech #PreK12 #SchoolLeadership #EdTechInvestment #AIinEducation

While the world races to scale artificial intelligence, we asked a different question: What would it look like if those closest to students, teachers, led the conversation about how AI shows up in schools? The result: The Teacher-Created AI Guidelines — born out of the Codesign Collective, an innovation from Leanlab Education, with 228 Accelerator as a facilitation partner. These guidelines are not corporate white papers or top-down policy briefs. They are crowdsourced human intelligence, built from the lived experiences, fears, hopes, and wisdom of real educators, designing for justice at the intersection of AI and learning. In a moment where hype outpaces humanity, these guidelines center: 1. Equity over efficiency 2. Agency over automation 3. Relationships over replacement 4. Design with—not for—communities Why does it matter? Because how we design AI now will shape who it serves — and who it leaves behind — for generations. Read the complete guidelines. Share them. Use them. And most importantly: let educators lead. #AI #Education #EquityXDesign #CodesignCollective #TeacherVoice #HumanIntelligence #EdTech #EthicalAI #LiberatoryDesign https://lnkd.in/ewmbbzrD

The K-12 AI Infrastructure is Broken. A New $26M Fund is Fixing It. Tired of EdTech products that ignore learning science? This is major news: A new $26 million grant program is launching to fund the open AI infrastructure needed to transform K-12 education. The future of learning won't be achieved by closed-source algorithms. This fund is making AI for education a public utility, investing in openly-shared datasets, models, and benchmarks. This approach ensures technology serves students, not just profits, founding AI on responsibility first. This is your invitation to help guide that public infrastructure. The power of learning science and the rigor of education-specific AI must meet to ensure the products of tomorrow reflect the needs of all learners. AI built for teachers, not shareholders. Collaborative Partners: This initiative, managed by a team of research, data, and privacy experts, is led by Digital Promise alongside core partners: Learning Data Insights, LLC Driven Data Massive Data Institute at Georgetown University Catalyst @ Penn GSE 📢 Call to Action: Shape the Future of K-12 AI Start Creating: The program is actively asking you to define the problems worth solving. Respond to the Request for Information (RFI) before Monday, November 24, 2025. Define the Public Goods: Tell the program what openly-shared datasets and models are most needed to make AI equitable and a shared public resource. Teachers: Claim Your Voice: Submit comments to guide AI development and ensure utility over novelty. Share the Story: If every educator and technologist shares this RFI once, we can guarantee the best ideas—not just the loudest voices—shape the future of AI in K-12. Jeremy Roschelle, Rachel Dinkes, PhD, Brooke Stafford-Brizard, Stacey Pelika, Erin Stark, Natasha Tetruyeva 🇺🇦, Sara Schapiro, Amber Oliver, Barbara Pape, Eileen Rudden, Neal Kingston, Janice Gobert, Stephen Plank, Jessica Tsang, Edward Metz, Lewis Leiboh, Matthew Muench, Daniel Jarratt, Jean-Claude Brizard, Erik Burmeister, Prasad (Pram) Ram, Ulrich Boser, Joel Rose, Alex Sarlin, Babak Mostaghimi, Steve Shapiro, Sunil Gunderia, Erin Higgins, Michael Klein, Julia Rafal-Baer, Chris L., Eric Nentrup, Ed Dieterle, Bryan Setser, Jonathan Steinberg, Susan Patrick, Pat Yongpradit,

🚨 𝗦𝘁𝗼𝗽 𝗯𝘂𝘆𝗶𝗻𝗴 𝘀𝗵𝗶𝗻𝘆 𝘁𝗼𝗼𝗹𝘀. 𝗦𝘁𝗮𝗿𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝘄𝗼𝗿𝗸 𝗦𝗵𝗮𝗽𝗲 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 whitepaper from Bett, ASCL and Educate Ventures highlights the same gaps across schools: ⚠️ Four recurring problems • 𝗡𝗼 𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆, leaving schools to decide on AI and EdTech alone • 𝗗𝗲𝘃𝗶𝗰𝗲𝘀 𝗮𝗿𝗿𝗶𝘃𝗶𝗻𝗴 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴, creating frustration and underuse • 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 squeezed into full timetables, with leaders calling for protected, mandatory training time • 𝗢𝗻𝗲-𝗼𝗳𝗳 𝗴𝗿𝗮𝗻𝘁𝘀 that block long term planning 💡 What the report makes clear Technology only improves learning when schools invest in more than devices. Invest in: • 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 • 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗳𝘂𝗻𝗱𝗶𝗻𝗴 • 𝗦��𝗮𝗳𝗳 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 🔎 Why EdTech leadership matters • Aligns technology with learning goals • Secures sustained resources and a clear strategy • Embeds training so tools support teaching rather than sit unused ❓ Question How is your school balancing tools, training and strategy? 📄 Download the whitepaper (PDF) https://lnkd.in/ebg_rdjm

Mike Yates of Teach For America’s Reinvention Lab has a litmus tech for edtech: If it doesn’t create space for meaningful human moments, it doesn’t belong in schools. The best learning models are co-designed with young people—not imposed on them. “The school model that was right for them was the one they got to help shape,” Mike shared with the City Club of Cleveland. He challenged educators to: 🤖 Use AI to enable collaboration, movement, and relationships, not recreate computer labs 🤖 Design for time, curiosity, and practice—not adult comfort 🤖Replace bans with developmental guardrails, while being explicit that AI is not human Watch the full conversation on PBS to hear Mike’s perspective on AI, civic learning, and what schools must rethink to truly serve today’s learners. https://lnkd.in/ggJggDc5

In an insightful interview with Elvis Boniface, M.A.(Ed) for Edugist, Stephen Jull captured a shift underway in education. AI has ended the old edtech dependency model, as teachers can now build the tools they once waited for companies to deliver. Three quick insights. Teacher agency is rising. The move is from AI literacy to AI creation. Educators become builders. Access defines equity. Without devices and connectivity, AI’s promise is empty. Infrastructure must be a core policy priority. Educators must shape AI. Teachers and parents need real influence over how AI enters classrooms and homes. The takeaway is clear. AI in education works only when it expands agency, closes access gaps, and is guided by the people closest to learning. #AIinEducation #TeacherAgency #EdTech #EducationalEquity #AIEthics #FutureofLearning https://lnkd.in/gkms9XfU